Abstract
The paper presents a genetic fuzzy rule-based technique for the modelling of generalized time series (containing both, numerical and non-numerical, qualitative data) which are a comprehensive source of information concerning the behaviour of many complex systems and processes. The application of the proposed approach to the fuzzy rule-based modelling of an industrial gas furnace system using measurement data available from the repository at the http://www.stat.wisc.edu/~reinsel/bjr-data (the so-called Box-Jenkins’ benchmark) is also presented.
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References
Baczyński, M., Jayaram, B.: Fuzzy Implications. Springer, Heidelberg (2008)
Box, G.E., Jenkins, G.M.: Time Series Analysis: Forecasting and Control. Holden Day, San Francisco (1970)
Cordon, O., Herrera, F., Hoffmann, F., Magdalena, L.: Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases. World Scientific, Singapore (2001)
Gorzałczany, M.B.: Computational Intelligence Systems and Applications, Neuro-Fuzzy and Fuzzy Neural Synergisms. Physica-Verlag, Springer-Verlag Co., Heidelberg, New York (2002)
Gorzałczany, M.B., Rudziński, F.: A Modified Pittsburg Approach to Design a Genetic Fuzzy Rule-Based Classifier from Data. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010. LNCS, vol. 6113, pp. 88–96. Springer, Heidelberg (2010)
Gorzałczany, M.B., Rudziński, F.: Measurement data in genetic fuzzy modelling of dynamic systems. Pomiary, Automatyka, Kontrola 56(12), 1420–1423 (2010)
Gorzałczany, M.B., Rudziński, F.: Accuracy vs. Interpretability of Fuzzy Rule-Based Classifiers: An Evolutionary Approach. In: Rutkowski, L., et al. (eds.) ICAISC 2012. LNCS, vol. 7269, pp. 222–230. Springer, Heidelberg (2012)
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Gorzałczany, M.B., Rudziński, F. (2012). Genetic Fuzzy Rule-Based Modelling of Dynamic Systems Using Time Series. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Swarm and Evolutionary Computation. EC SIDE 2012 2012. Lecture Notes in Computer Science, vol 7269. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29353-5_27
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DOI: https://doi.org/10.1007/978-3-642-29353-5_27
Publisher Name: Springer, Berlin, Heidelberg
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